Test method and device for unmanned equipment, electronic equipment and storage medium

Abstract

The invention discloses a test method and device for unmanned equipment, electronic equipment and a storage medium, and relates to the technical field of unmanned. The unmanned equipment is provided with an auxiliary device, the auxiliary device is connected with an upper computer, the auxiliary device comprises a data acquisition device, and the method comprises the following steps: receiving first data of the unmanned equipment output by the data acquisition device, and processing the first data according to an input data type of a control program for performing unmanned driving on the unmanned equipment, obtaining second data with the input data type; determining a first data frequency of the data acquisition device according to the first data; judging whether the data acquisition device has a fault at a hardware protocol level according to the first data frequency; determining a second data frequency of the data acquisition device according to the second data, and reading target data corresponding to the process of executing the preset action by the unmanned equipment in the second data; and according to the second data frequency and the target data, judging whether the data acquisition device has a data driving layer fault or not.

Description

Technical Field

[0001] The present disclosure relates to the field of unmanned technology, and in particular to a testing method for unmanned equipment, a testing device for unmanned equipment, an electronic device, and a computer-readable storage medium. Background Art

[0002] With the development of artificial intelligence, unmanned technology is increasingly being applied across various fields. To ensure the effectiveness of unmanned control algorithms on unmanned equipment, these devices must first be retrofitted with intelligent technology. This can include installing auxiliary devices to collect data. Factors such as the installation location, hardware quality, and performance of these auxiliary devices can affect the effectiveness of unmanned control algorithms, necessitating effective testing of the quality of these intelligent retrofits. Summary of the Invention

[0003] The present disclosure provides a testing method for unmanned equipment, a testing device for unmanned equipment, an electronic device, and a computer-readable storage medium to solve or at least partially solve the above-mentioned problems, as follows.

[0004] In a first aspect, embodiments of the present disclosure provide a testing method for an unmanned device, wherein the unmanned device is configured with an auxiliary device for unmanned driving of the unmanned device, the auxiliary device being connected to a host computer, the auxiliary device including a data acquisition device, the method being applied to the host computer, the method comprising:

[0005] receiving first data of the unmanned device output by the data acquisition device, and processing the first data according to an input data type of a control program for unmanned driving of the unmanned device to obtain second data having the input data type;

[0006] determining a first data frequency of the data acquisition device according to the first data;

[0007] Determining whether the data acquisition device has a hardware protocol level fault according to the first data frequency;

[0008] determining a second data frequency of the data acquisition device according to the second data, and reading target data corresponding to a process in which the unmanned equipment performs a preset action from the second data;

[0009] It is determined whether the data acquisition device has a data drive level fault according to the second data frequency and the target data.

[0010] In a second aspect, an embodiment of the present disclosure further provides a testing device for unmanned equipment, wherein the unmanned equipment is configured with an auxiliary device for unmanned driving of the unmanned equipment, the auxiliary device being connected to a host computer, the auxiliary device including a data acquisition device, the testing device for the unmanned equipment being deployed on the host computer, and the testing device for the unmanned equipment comprising:

[0011] a data receiving and processing module, configured to receive first data of the unmanned device output by the data acquisition device, and process the first data according to an input data type of a control program for unmanned driving of the unmanned device to obtain second data having the input data type;

[0012] a frequency determination module, configured to determine a first data frequency of the data acquisition device according to the first data;

[0013] a first judging module, configured to judge whether the data acquisition device has a hardware protocol fault according to the first data frequency;

[0014] a frequency determination and data reading module, configured to determine a second data frequency of the data acquisition device according to the second data, and to read target data corresponding to a process in which the unmanned equipment performs a preset action in the second data;

[0015] The second judgment module is used to judge whether the data acquisition device has a data drive level fault according to the second data frequency and the target data.

[0016] In a third aspect, an embodiment of the present disclosure further provides an electronic device, comprising: a processor, a memory, and computer program instructions stored in the memory and executable on the processor;

[0017] When the processor executes the computer program instructions, the testing method for unmanned equipment as described in the first aspect above is implemented.

[0018] In a fourth aspect, an embodiment of the present disclosure further provides a computer-readable storage medium, in which computer program instructions are stored. When the computer program instructions are executed by a processor, they are used to implement the testing method for unmanned equipment as described in the first aspect above.

[0019] Compared with the prior art, the exemplary embodiments of the present disclosure have the following beneficial effects:

[0020] In the test method for unmanned equipment provided by the present disclosure, a host computer can receive first data of the unmanned equipment output by a data acquisition device, and process the first data according to the input data type of the control program for unmanned driving of the unmanned equipment to obtain second data of the input data type; determine the first data frequency of the data acquisition device according to the first data; determine whether the data acquisition device has a hardware protocol level fault according to the first data frequency; determine the second data frequency of the data acquisition device according to the second data, and read the target data corresponding to the process of the unmanned equipment performing a preset action in the second data; and determine whether the data acquisition device has a data drive level fault according to the second data frequency and the target data. In the present disclosure, by determining whether the data frequency of the data acquisition device installed on the unmanned equipment at the data output level meets the business requirements of unmanned driving, and determining whether the data frequency of the data acquisition device at the data drive layer output level and the data itself meet the business requirements of unmanned driving, the quality of the intelligent transformation of the unmanned equipment is tested. In the present disclosure, there is no need to test the function of the upper-level unmanned driving control program, and the unmanned equipment is directly tested at the intelligent transformation level, which reduces the safety risk in the unmanned equipment testing process, shortens the problem location link, and improves the testing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a schematic diagram of a device system provided by one embodiment of the present disclosure;

[0022] Figure 2 This is a flowchart of a testing method for unmanned equipment provided by one embodiment of the present disclosure;

[0023] Figure 3 This is a block diagram of a testing device for unmanned equipment provided by one embodiment of the present disclosure;

[0024] Figure 4 This is a logical structure diagram of an electronic device for implementing testing for unmanned equipment, provided in one embodiment of the present disclosure. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical solutions and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. The components of the embodiments of the present disclosure generally described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present disclosure provided in the drawings is not intended to limit the scope of the disclosure for which protection is sought, but merely represents selected embodiments of the present disclosure. Based on the embodiments of the present disclosure, every other embodiment obtained by those skilled in the art without making creative work falls within the scope of protection of the present disclosure.

[0026] The terms "a", "an", "the" and "said" are used in this specification to indicate the presence of one or more elements / components / etc.; the terms "including" and "having" are used to express open-ended inclusion and mean that additional elements / components / etc. may exist in addition to the listed elements / components / etc.; the terms "first" and "second" etc. are used only as labels and are not intended to limit the quantity of their objects.

[0027] It should be understood that in the embodiments of the present disclosure, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent three situations: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the previous and subsequent associated objects are in an "or" relationship. "Including A, B and / or C" means including any one, any two, or any three of A, B, and C.

[0028] It should be understood that in the embodiments of the present disclosure, "B corresponding to A," "B corresponding to A," "A corresponds to B," or "B corresponds to A" means that B is associated with A and B can be determined based on A. Determining B based on A does not mean determining B based solely on A; B can also be determined based on A and / or other information.

[0029] Before describing the embodiments of the present disclosure in detail, the related art will be further introduced.

[0030] In related technologies, the testing process after the unmanned equipment is intelligently transformed can be as follows: the tester will install the control program used for unmanned driving of the unmanned equipment into the unmanned equipment, and start all related equipment and services used for unmanned driving, and then verify whether the unmanned equipment has any faults through end-to-end functional testing.

[0031] However, this end-to-end functional testing is essentially a test of the specific functions of unmanned equipment, so it will have the following problems:

[0032] 1. Difficulty in fault location: When an abnormality is detected in the end-to-end functional test results, it is difficult to determine whether the problem lies with the auxiliary device or the control program, let alone the hardware protocol or data driver level of the auxiliary device.

[0033] 2. High safety risks: Directly driving the control program for testing when it is impossible to determine whether the auxiliary device is functioning properly may cause certain safety issues. For example, the unmanned equipment may cause the control program to make incorrect judgments due to problems such as the installation location or data frequency not meeting the requirements, causing the unmanned equipment to collide with its own structure or with objects in the environment.

[0034] 3. Low testing efficiency: End-to-end functional testing requires testing each function of the unmanned equipment in sequence. Different functions use the same auxiliary devices, resulting in redundant testing. When problems are discovered during the test, the troubleshooting link is long and the positioning time is long.

[0035] The above-mentioned end-to-end functional testing method has high requirements for testers and low testing efficiency. The testers' levels are uneven, which may lead to problems such as omissions and misdetection, which is not conducive to the quality and efficiency of batch testing. In addition, this method introduces security risks. Even the smallest risk probability is worrying in the context of large-base testing.

[0036] In summary, the present disclosure provides a testing method for unmanned equipment. This method can skip the functional testing of the upper-level unmanned driving control program and directly perform intelligent transformation testing on the unmanned equipment, thereby reducing the safety risks during the functional testing process. In addition, by directly testing from the bottom layer of intelligent transformation, the positioning link is greatly shortened, thereby improving the testing efficiency. Optionally, this method can also perform targeted testing on the characteristics of each auxiliary device installed, thereby avoiding redundant testing.

[0037] After eliminating problems at the level of intelligent transformation of unmanned equipment, functional testing of the upper-level unmanned drive control program can be performed. If problems occur, the upper-level control layer can be checked, which can further improve testing efficiency.

[0038] Figure 1 A schematic diagram of a device system provided by one embodiment of the present disclosure is shown in FIG. Figure 1 As shown, the equipment system includes unmanned equipment 10, one or more auxiliary devices 20 ( Figure 1Only two auxiliary devices 20 are used as an example in the figure) and a host computer 30. The auxiliary device 20 is configured on the unmanned device 10 and is used to perform unmanned driving of the unmanned device 10. The auxiliary device 20 is connected to the host computer 30. The auxiliary device 20 includes a data acquisition device 21 and a slave computer 22. The data acquisition device 21 is used to collect motion data, environmental data, etc. of the unmanned device, which are the basic data required for unmanned driving decision-making. The slave computer 22 is connected to the unmanned device 10 and can be used to control the unmanned device 10 to perform actions in response to control instructions received from the host computer 30.

[0039] In the present disclosure, a control program for unmanned driving of the unmanned device 10 may also be installed in the host computer 30. After completing all tests on the unmanned device 10, the host computer 30 runs the control program, which can make driving decisions based on the data provided by the data acquisition device 21, thereby sending control instructions to the lower computer 22. The lower computer 22 can control the unmanned device 10 to perform corresponding actions in response to the control instructions, thereby realizing unmanned driving of the unmanned device 10.

[0040] In an optional embodiment of the present disclosure, the unmanned equipment 10 may include one or more of the following: an unmanned loader, an unmanned excavator, an unmanned forklift, an unmanned shovel, and an unmanned robot.

[0041] In an optional embodiment of the present disclosure, the data acquisition device 21 may include one or more of the following: a sensor (e.g., a hydraulic pressure sensor), a measuring encoder (e.g., a steering angle encoder), a speedometer (e.g., a wheel speedometer), and a shooting device (e.g., a camera).

[0042] In an optional embodiment of the present disclosure, the lower computer 22 may include one or more of the following: a single chip microcomputer, a PLC (Programmable Logic Controller), or an FPGA (Field-Programmable Gate Array).

[0043] In an optional embodiment of the present disclosure, the host computer 30 may include one or more of the following: a terminal (such as a computer, a mobile phone), a server (such as a cloud server).

[0044] It should be understood that the above optional embodiments do not limit the present disclosure.

[0045] Figure 2 A flow chart of a test method for unmanned equipment provided by one embodiment of the present disclosure is shown. The test method for unmanned equipment is applied to the host computer described in the above-mentioned equipment system, such as Figure 2As shown, in one embodiment of the present disclosure, the testing method for unmanned equipment may include the following steps S101 to S105.

[0046] Step S101: receiving first data of the unmanned equipment output by the data acquisition device, and processing the first data according to the input data type of the control program for unmanned driving of the unmanned equipment to obtain second data having the input data type.

[0047] In the present disclosure, the data acquisition device can collect data from unmanned equipment at a certain collection frequency to obtain collected data. The data acquisition device can process the collected data to obtain the first data required by the host computer, and then output the first data to the host computer connected to the data acquisition device.

[0048] After the host computer receives the first data output by the data acquisition device, it can process the first data. The processing includes data type conversion for the first data, so that the data type of the first data can be converted into a data type that can be processed by the control program for unmanned driving of unmanned equipment.

[0049] Specifically, the host computer can parse the first data according to the hardware bottom layer protocol of the data acquisition device, and then encapsulate the parsed data into the data format required by the input data type of the control program to obtain the second data.

[0050] For example, assuming that the hardware underlying protocol of the data acquisition device is the CAN protocol (Controller Area Network, a serial data communication protocol), the upper computer can be configured with a ROS system (Robot Operating System), and the communication mechanism of the ROS system is a publish-subscribe mechanism based on topics. The data output by a data acquisition device is parsed and transformed by the data driver layer of the ROS system, and finally output to a topic. For example, generally one data acquisition device corresponds to one topic, and it is also possible that the data of multiple data acquisition devices are fused and output to one topic. The data driver layer can publish a message to the topic. Accordingly, the data acquisition device can output the first data of the CAN type through the CAN bus, the upper computer can parse the first data according to the CAN protocol, and then encapsulate the parsed data into the ROS Message type to obtain the second data of the ROSMessage type.

[0051] Step S102: determining a first data frequency of the data acquisition device according to the first data.

[0052] In this step, the host computer can determine the first data frequency of the data acquisition device based on the first data directly output by the data acquisition device, wherein the first data frequency is the data output frequency of the data acquisition device, and the data output frequency of the data acquisition device is less than or equal to the data acquisition frequency of the data acquisition device. If the first data received within a certain period of time is read, the first data frequency f can be determined based on the amount M of first data received within the period of time and the duration T of the period of time, where f = M / T.

[0053] Step S103: Determine whether the data acquisition device has a hardware protocol fault according to the first data frequency.

[0054] The first data frequency of the data acquisition device can reflect the data output performance of the data acquisition device. By judging whether the first data frequency meets the frequency range required by the unmanned control program, it can be determined whether the data acquisition device has a hardware protocol level fault.

[0055] Among them, failures at the hardware protocol level include failures of the hardware itself and failures of the hardware's underlying protocol. If there is a problem with either the hardware itself or the hardware's underlying protocol of the data acquisition device, it means that there is a problem at the hardware protocol level of the data acquisition device.

[0056] In an optional embodiment of the present disclosure, the above step S103 can be specifically implemented by the following steps S1031 to S1033, including:

[0057] Step S1031: Determine whether the first data frequency is within a first frequency range preset for the data acquisition device.

[0058] The first frequency range can be set based on the control program's requirements for the data acquisition device. The first data serves as the basis for data before entering the control program. Therefore, the first data frequency of the data acquisition device determines whether sufficient data can enter the control program to make unmanned driving decisions. Therefore, in this step, it is necessary to determine whether the first data frequency is within the first frequency range set based on the control program's requirements for the data acquisition device.

[0059] Step S1032: If the first data frequency is within a first frequency range preset for the data acquisition device, it is determined that there is no hardware protocol level failure in the data acquisition device.

[0060] If the first data frequency is within the first frequency range preset for the data acquisition device, it means that the data output frequency of the data acquisition device meets the requirements of the control program for the data acquisition device. Therefore, it can be determined that the data acquisition device does not have its own hardware failure and hardware underlying protocol failure.

[0061] Optionally, if the first data frequency is within the first frequency range preset for the data acquisition device, the test log can be displayed through the console of the host computer (the command line interface of the operating system) to indicate that there is no hardware protocol level failure in the data acquisition device.

[0062] Step S1033: If the first data frequency is not within a first frequency range preset for the data acquisition device, it is determined that a hardware protocol fault exists in the data acquisition device.

[0063] If the first data frequency is not within the first frequency range preset for the data acquisition device, it means that the data output frequency of the data acquisition device cannot meet the requirements of the control program for the data acquisition device. Therefore, it can be determined that there is a hardware protocol level fault in the data acquisition device. Based on the test results of the hardware protocol level fault in the data acquisition device, it can be further checked whether there is a fault in the data acquisition device's own hardware or in the underlying hardware protocol.

[0064] Optionally, if the first data frequency is not within the first frequency range preset for the data acquisition device, the test log can be displayed through the console of the host computer to indicate that there is a hardware protocol level failure in the data acquisition device and stop subsequent steps.

[0065] Step S104: determining a second data frequency of the data acquisition device according to the second data, and reading target data corresponding to a process of the unmanned equipment performing a preset action in the second data.

[0066] In an optional embodiment of the present disclosure, if the first data frequency is within a first frequency range preset for the data acquisition device, the second data frequency of the data acquisition device can be determined based on the second data, and the target data of the process corresponding to the unmanned equipment performing the preset action in the second data can be read.

[0067] That is, in this embodiment, after determining that there is no hardware protocol level fault in the data acquisition device, subsequent fault judgments at other levels can be performed, thereby improving test efficiency.

[0068] Among them, the second data is data that can be processed by the control program by processing the first data output by the data frequency. Therefore, the second data frequency is also the data output frequency of the data acquisition device reflected at the data receiving level of the control program.

[0069] In the present disclosure, the data collection device can collect data from the unmanned device regardless of whether the unmanned device is performing an action or not. Therefore, the second data can include the second data corresponding to the unmanned device not performing an action and the second data corresponding to the unmanned device performing an action, wherein the second data corresponding to the unmanned device performing an action includes target data corresponding to the process of the unmanned device performing a preset action. The preset action can be set according to the type of data that the data collection device can output.

[0070] For example, taking the unmanned equipment as an unmanned loader, the data acquisition device may be a steering angle encoder, and the data type that the steering angle encoder can output is an angle value. The preset action may include the front axle of the unmanned loader turning from the base position to the left extreme position and to the right extreme position respectively. Accordingly, the steering angle encoder may output a first steering angle value for turning to the left extreme position and a second steering angle value for turning to the right extreme position.

[0071] For example, taking the unmanned equipment as an unmanned loader, the data acquisition device may be a hydraulic pressure sensor, and the data type that the hydraulic pressure sensor can output is a pressure value. The preset action may include the unmanned loader reaching the extreme position of the joint touching the ground and reaching the extreme position of the joint being raised. Accordingly, the hydraulic pressure sensor may output a first pressure value when the joint reaches the extreme position of the joint touching the ground, and a second pressure value when the joint reaches the extreme position of the joint being raised.

[0072] For example, taking the unmanned equipment as an unmanned loader, the data acquisition device may be a wheel speed meter, and the data type that the wheel speed meter can output is the wheel speed value. The preset action may include switching the gear of the unmanned loader to 1st gear, and then idling the unmanned loader after releasing the brake (that is, the engine of the unmanned loader runs at the lowest speed without applying the accelerator). Accordingly, the wheel speed meter can output the wheel speed value of the unmanned loader when idling.

[0073] For example, taking the unmanned equipment as an unmanned loader, the data acquisition device may be a camera, and the type of data that the camera can output is an image. The preset action may include the unmanned loader passing through a preset path at a preset speed. Accordingly, the camera can output the environmental image captured when the unmanned loader passes through the preset path.

[0074] In the present disclosure, the target data of the process corresponding to the unmanned equipment performing the preset action in the second data can also be read to determine whether the host computer can correctly convert the output data of the data acquisition device into data that can be processed by the control program.

[0075] Step S105: Determine whether the data acquisition device has a data drive level fault according to the second data frequency and the target data.

[0076] The second data frequency can reflect whether the input data of the control program meets the data frequency required by the business, and the target data can reflect whether the data output by the data acquisition device when the unmanned equipment performs a specific action can be correctly converted. Therefore, in this step, it can be judged whether there is a data-driven level failure in the data acquisition device based on the second data frequency and the target data. The data-driven level failure includes the data not meeting the data volume requirements of the control program to achieve unmanned driving, and the data cannot be processed correctly.

[0077] In an optional embodiment of the present disclosure, the above step S105 can be specifically implemented by the following steps S1051 to S1053, including:

[0078] Step S1051: Determine whether the target data differs from the reference data preset for the data acquisition device by more than a preset error range, and determine whether the second data frequency is within the second frequency range preset for the data acquisition device.

[0079] The benchmark data can be obtained by controlling (manually or automatically) the test equipment to perform a preset action while ensuring that the auxiliary devices of the test equipment are fault-free. The test equipment can be a device of the same brand and model as the unmanned equipment. Accordingly, benchmark data corresponding to multiple auxiliary devices can be stored for each brand and model. When determining whether the target data differs from the benchmark data preset for the data acquisition device by more than a preset error range, the host computer can first search the brand and model library for all benchmark data corresponding to the brand and model of the unmanned equipment being tested, and then make a judgment based on the benchmark data corresponding to each auxiliary device of the unmanned equipment.

[0080] Regarding the step of determining whether the target data differs from the baseline data preset for the data acquisition device by more than a preset error range, two optional implementations are provided below. It can be understood that this step can also be implemented in other ways, and this disclosure does not specifically limit this.

[0081] In an optional embodiment of the present disclosure, assuming the baseline data is a, an error ratio b% can be predetermined for the data acquisition device. If the target data is within the data interval [ab%, a+b%], it can be determined that the target data does not differ from the baseline data preset for the data acquisition device by more than the preset error range. If the target data is not within the data interval [ab%, a+b%], it can be determined that the target data does not differ from the baseline data preset for the data acquisition device by more than the preset error range.

[0082] In another optional embodiment of the present disclosure, assuming the reference data is a, an error value c can be predetermined for the data acquisition device. If the absolute value of the difference between the target data d and the reference data a is |da|≤c, it can be determined that the target data does not differ from the reference data preset for the data acquisition device by more than a preset error range. If the absolute value of the difference between the target data d and the reference data a is |da|>c, it can be determined that the target data does differ from the reference data preset for the data acquisition device by more than a preset error range.

[0083] In addition, in this step, illustratively, the second frequency range may be the same as the first frequency range.

[0084] Exemplarily, the second frequency range may also be different from the first frequency range.

[0085] In the present disclosure, the first data frequency and the second data frequency are allowed to have a certain floating space. This is because the data frequency will fluctuate due to factors such as the baud rate. Therefore, the first data frequency and the second data frequency can be determined to meet the requirements as long as they meet a certain frequency range.

[0086] In addition, in the present disclosure, the second data frequency does not have to be the same as the first data frequency. This is because the host computer can supplement or delete the first data within a reasonable range, which will make the second data frequency different from the first data frequency. Therefore, as long as the first data frequency and the second data frequency each meet a certain frequency range, they can be determined to meet the requirements, and it is not necessary for the two to be consistent.

[0087] In this way, a testing mechanism can be provided for unmanned equipment that meets business requirements without being too harsh.

[0088] Step S1052: If the target data does not differ from the preset reference data for the data acquisition device by more than the preset error range, and the second data frequency is within the preset second frequency range for the data acquisition device, it is determined that there is no data drive level fault in the data acquisition device.

[0089] In this step, if the target data does not differ from the benchmark data preset for the data acquisition device by more than the preset error range, and the second data frequency is within the second frequency range preset for the data acquisition device, that is, the target data conversion is correct and the second data frequency meets the business requirements, then it can be determined that there is no data-driven level failure in the data acquisition device.

[0090] Optionally, if the target data does not differ from the benchmark data preset for the data acquisition device by more than a preset error range, and the second data frequency is within the second frequency range preset for the data acquisition device, the test log can be displayed through the console of the host computer to indicate that there is no data-driven level failure in the data acquisition device.

[0091] Step S1053: If the target data differs from the preset reference data for the data acquisition device by more than a preset error range, or the second data frequency is not within the preset second frequency range for the data acquisition device, it is determined that the data acquisition device has a data drive level fault.

[0092] In this step, if the target data differs from the benchmark data preset for the data acquisition device by more than a preset error range, or the second data frequency is not within the second frequency range preset for the data acquisition device, that is, the target data conversion is incorrect or the second data frequency does not meet the business requirements, as long as at least one of the two situations occurs, it can be determined that there is a data-driven level failure in the data acquisition device.

[0093] Optionally, if the target data differs from the benchmark data preset for the data acquisition device by more than a preset error range, or the second data frequency is not within the second frequency range preset for the data acquisition device, the test log can be displayed through the console of the host computer to indicate that there is a data-driven level fault in the data acquisition device.

[0094] In the present disclosure, there is no limitation on the execution order of the three judgment steps of judging whether there is a hardware protocol level fault in the data acquisition device according to the first data frequency, judging whether the target data differs from the benchmark data preset for the data acquisition device by more than a preset error range, and judging whether the second data frequency is within the second frequency range preset for the data acquisition device.

[0095] In an optional example, the above three judgment steps can be performed in the following order: first, determine whether the data acquisition device has a hardware protocol level failure based on the first data frequency; then determine whether the target data differs from the benchmark data preset for the data acquisition device by more than a preset error range; and then determine whether the second data frequency is within the second frequency range preset for the data acquisition device.

[0096] In an optional example, the above three judgment steps can be performed in the following order: first, determine whether the data acquisition device has a hardware protocol level fault based on the first data frequency; then determine whether the second data frequency is within the second frequency range preset for the data acquisition device; and then determine whether the target data differs from the benchmark data preset for the data acquisition device by more than a preset error range.

[0097] In an optional example, the above three judgment steps can be performed in the following order: first, determine whether the target data differs from the benchmark data preset for the data acquisition device by more than a preset error range; then determine whether the second data frequency is within the second frequency range preset for the data acquisition device; and then determine whether the data acquisition device has a hardware protocol level failure based on the first data frequency.

[0098] In an optional example, the above three judgment steps can be performed in the following order: first, determine whether the second data frequency is within the second frequency range preset for the data acquisition device; then, determine whether the data acquisition device has a hardware protocol level failure based on the first data frequency; and then determine whether the target data differs from the benchmark data preset for the data acquisition device by more than a preset error range.

[0099] Furthermore, the slave computer can be used to convert pulses from the master computer into electrical signals, thereby controlling the opening and closing of the solenoid valves, and thereby driving the movement of the various joints of the unmanned device. In an optional embodiment of the present disclosure, since the slave computer is the direct control device of the unmanned device, it will also affect the effectiveness of the unmanned driving. Therefore, it is also necessary to test the slave computer. Accordingly, when the auxiliary device includes the slave computer, the testing method for the unmanned device can also include the following steps S106 to S109.

[0100] Step S106: Generate a target control instruction for controlling the unmanned equipment to perform a target action according to the output instruction type of the control program.

[0101] In this step, the host computer can encapsulate the control parameters used to control the unmanned equipment to perform the target action, and obtain the target control instructions for controlling the unmanned equipment to perform the target action. The instruction type of the target control instructions is the same as the output instruction type of the control program used for unmanned driving of the unmanned equipment.

[0102] Step S107: Send the target control instruction to the lower computer, so that the lower computer controls the unmanned equipment to perform an action in response to the target control instruction.

[0103] Next, the upper computer can send the encapsulated target control instruction to the lower computer, and then the lower computer can control the unmanned equipment to perform actions in response to the target control instruction.

[0104] Step S108: Determine the action performed by the unmanned device.

[0105] In this step, the host computer needs to determine the action performed by the unmanned device under the control of the target control instruction. In an optional embodiment, after manually observing the action performed by the unmanned device, the action information of the action performed by the unmanned device, such as the action code, can be input into the host computer, so that the host computer can determine what action the unmanned device performed under the control of the target control instruction based on the input action information. In another optional embodiment, a fixed-position camera device can be used to capture pictures or videos of the unmanned device performing the action, and then the host computer performs action recognition based on the pictures or videos to determine what action the unmanned device performed under the control of the target control instruction.

[0106] Step S109: Determine whether the lower computer has a fault based on the action performed by the unmanned equipment.

[0107] In an optional implementation of the present disclosure, it can be determined whether the lower computer has a fault through the following steps S1091 to S1093.

[0108] Step S1091: Determine whether the action performed by the unmanned device is the target action.

[0109] Step S1092: If the action performed by the unmanned equipment is the target action, it is determined that there is no fault in the lower computer.

[0110] Step S1093: If the action performed by the unmanned equipment is not the target action, it is determined that the lower computer has a fault.

[0111] In this embodiment, the host computer can determine whether the action performed by the unmanned device is the target action. If the action performed by the unmanned device is the target action, it means that the unmanned device can correctly perform the action instructed by the target control instruction under the control of the target control instruction, and therefore, it can be determined that there is no fault in the lower computer. If the action performed by the unmanned device is not the target action, it means that the unmanned device cannot correctly perform the action instructed by the target control instruction under the control of the target control instruction, and therefore, it can be determined that there is a fault in the lower computer.

[0112] In the test method for unmanned equipment provided by the present disclosure, a host computer can receive first data of the unmanned equipment output by a data acquisition device, and process the first data according to the input data type of the control program for unmanned driving of the unmanned equipment to obtain second data of the input data type; determine the first data frequency of the data acquisition device according to the first data; determine whether the data acquisition device has a hardware protocol level fault according to the first data frequency; determine the second data frequency of the data acquisition device according to the second data, and read the target data corresponding to the process of the unmanned equipment performing a preset action in the second data; and determine whether the data acquisition device has a data drive level fault according to the second data frequency and the target data. In the present disclosure, by determining whether the data frequency of the data acquisition device installed on the unmanned equipment at the data output level meets the business requirements of unmanned driving, and determining whether the data frequency of the data acquisition device at the data drive layer output level and the data itself meet the business requirements of unmanned driving, the quality of the intelligent transformation of the unmanned equipment is tested. In the present disclosure, there is no need to test the function of the upper-level unmanned driving control program, and the unmanned equipment is directly tested at the intelligent transformation level, which reduces the safety risk in the unmanned equipment testing process, shortens the problem location link, and improves the testing efficiency.

[0113] Corresponding to the test method for unmanned equipment provided in the embodiment of the present disclosure, the embodiment of the present disclosure also provides a test device for unmanned equipment, wherein the unmanned equipment is equipped with an auxiliary device for unmanned driving of the unmanned equipment, the auxiliary device is connected to a host computer, the auxiliary device includes a data acquisition device, and the test device for unmanned equipment is deployed on the host computer. Figure 3 As shown, the testing device 700 for unmanned equipment includes:

[0114] a data receiving and processing module 701 for receiving first data of the unmanned device output by the data acquisition device, and processing the first data according to an input data type of a control program for unmanned driving of the unmanned device to obtain second data having the input data type;

[0115] A frequency determination module 702 is configured to determine a first data frequency of the data acquisition device according to the first data;

[0116] A first judgment module 703 is configured to judge whether the data acquisition device has a hardware protocol fault according to the first data frequency;

[0117] a frequency determination and data reading module 704, configured to determine a second data frequency of the data acquisition device according to the second data, and to read target data corresponding to a process in which the unmanned equipment performs a preset action from the second data;

[0118] The second judgment module 705 is used to judge whether the data acquisition device has a data drive level fault according to the second data frequency and the target data.

[0119] Optionally, the first judgment module includes:

[0120] a first judging submodule, configured to judge whether the first data frequency is within a first frequency range preset for the data acquisition device;

[0121] The first test result determination submodule is configured to determine that there is no hardware protocol level failure in the data acquisition device if the first data frequency is within the first frequency range preset for the data acquisition device.

[0122] Optionally, the first judgment module further includes:

[0123] The second test result determination submodule is configured to determine that a hardware protocol level fault exists in the data acquisition device if the first data frequency is not within the first frequency range preset for the data acquisition device.

[0124] Optionally, the frequency determination and data reading module is specifically used to:

[0125] If the first data frequency is within the first frequency range preset for the data acquisition device, the second data frequency of the data acquisition device is determined according to the second data, and the target data corresponding to the process of the unmanned equipment performing the preset action is read in the second data.

[0126] Optionally, the second judgment module includes:

[0127] a second judgment submodule, configured to judge whether the target data differs from the reference data preset for the data acquisition device by more than a preset error range, and to judge whether the second data frequency is within a second frequency range preset for the data acquisition device;

[0128] The third test result determination submodule is used to determine that there is no data-driven fault in the data acquisition device if the target data does not differ from the benchmark data preset for the data acquisition device by more than the preset error range, and the second data frequency is within the second frequency range preset for the data acquisition device.

[0129] Optionally, the second judgment module further includes:

[0130] The fourth test result determination submodule is used to determine that there is a data-driven fault in the data acquisition device if the target data differs from the benchmark data preset for the data acquisition device by more than the preset error range, or the second data frequency is not within the second frequency range preset for the data acquisition device.

[0131] Optionally, the auxiliary device includes a lower computer, which is connected to the unmanned device and is used to control the unmanned device to perform an action in response to a control instruction received from the upper computer. The test device for the unmanned device also includes:

[0132] A control instruction generation module, configured to generate a target control instruction for controlling the unmanned equipment to perform a target action according to an output instruction type of the control program;

[0133] A control instruction sending module, configured to send the target control instruction to the lower computer, so that the lower computer controls the unmanned equipment to perform an action in response to the target control instruction;

[0134] an action determination module, configured to determine an action to be performed by the unmanned device;

[0135] The lower computer test module is used to determine whether the lower computer has a fault according to the action performed by the unmanned equipment.

[0136] Optionally, the lower computer test module includes:

[0137] A third judgment submodule is used to judge whether the action performed by the unmanned device is the target action;

[0138] The fifth test result determination submodule is used to determine whether the lower computer has any fault if the action performed by the unmanned equipment is the target action.

[0139] Optionally, the lower computer test module further includes:

[0140] The sixth test result determination submodule is configured to determine that a fault exists in the lower computer if the action performed by the unmanned equipment is not the target action.

[0141] Optionally, the data acquisition device includes one or more of the following: a sensor, a measuring encoder, a speedometer, and a photographing device.

[0142] In the test device for unmanned equipment provided by the present disclosure, a host computer can receive first data of the unmanned equipment output by a data acquisition device, and process the first data according to the input data type of the control program for unmanned driving of the unmanned equipment to obtain second data of the input data type; determine a first data frequency of the data acquisition device according to the first data; determine whether the data acquisition device has a hardware protocol level fault according to the first data frequency; determine a second data frequency of the data acquisition device according to the second data, and read target data corresponding to the process of the unmanned equipment performing a preset action in the second data; and determine whether the data acquisition device has a data drive level fault according to the second data frequency and the target data. In the present disclosure, by determining whether the data frequency of the data acquisition device installed on the unmanned equipment at the data output level meets the business requirements of unmanned driving, and determining whether the data frequency of the data acquisition device at the data drive layer output level and the data itself meet the business requirements of unmanned driving, the quality of the intelligent transformation of the unmanned equipment is tested. In the present disclosure, there is no need to test the function of the upper-level unmanned driving control program, and the unmanned equipment is directly tested at the intelligent transformation level, which reduces the safety risk in the unmanned equipment testing process, shortens the problem location link, and improves the testing efficiency.

[0143] Next, an electronic device provided by an embodiment of the present disclosure is introduced. Figure 4 , Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present disclosure. The electronic device 800 may be equipped with the test device for unmanned equipment described in the embodiment of the present disclosure to implement the functions in the embodiment of the present disclosure. Specifically, the electronic device 800 includes: a receiver 801, a transmitter 802, a processor 803, and a memory 804 (the number of processors 803 in the execution device 800 may be one or more, Figure 4 (taking one processor as an example), the processor 803 may include an application processor 8031 ​​and a communication processor 8032. In some embodiments of the present disclosure, the receiver 801, the transmitter 802, the processor 803 and the memory 804 may be connected via a bus or other means.

[0144] The memory 804 may include a read-only memory and a random access memory, and provides instructions and data to the processor 803. A portion of the memory 804 may also include non-volatile random access memory (NVRAM). The memory 804 stores processor and operation instructions, executable modules, or data structures, or subsets or extended sets thereof. The operation instructions may include various operation instructions for implementing various operations.

[0145] Processor 803 controls the operation of the execution device. In specific applications, the various components of the execution device are coupled together via a bus system. In addition to a data bus, the bus system may also include a power bus, a control bus, and a status signal bus. However, for clarity, all bus systems are referred to as a bus system in the figure.

[0146] The methods disclosed in the above embodiments of the present disclosure can be applied to or implemented by the processor 803. The processor 803 can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by hardware integrated logic circuits in the processor 803 or by software instructions. The above processor 803 can be a general-purpose processor, a digital signal processor (DSP), a microprocessor, or a microcontroller, and can further include an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The processor 803 can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present disclosure. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in conjunction with the embodiments of the present disclosure can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in memory 804, and processor 803 reads information in memory 804 and, in conjunction with its hardware, completes the steps of the above method.

[0147] Receiver 801 can be used to receive input digital or character information and generate signal input related to executing device-related settings and function control. Transmitter 802 can be used to output digital or character information through the first interface. Transmitter 802 can also be used to send instructions to the disk pack through the first interface to modify data in the disk pack. Transmitter 802 can also include a display device such as a display screen.

[0148] In the embodiments of the present disclosure, application processor 8031 ​​within processor 803 is configured to execute the unmanned device testing method of the embodiments of the present disclosure. It should be noted that the specific manner in which application processor 8031 ​​executes each step is based on the same concept as the various method embodiments of the present disclosure, and the resulting technical effects are the same as those of the various method embodiments of the present disclosure. For details, please refer to the description of the method embodiments shown above in the present disclosure, and will not be repeated here.

[0149] The embodiment of the present disclosure also provides a chip for running instructions, which is used to execute the technical solution of the test method for unmanned equipment in the above embodiment.

[0150] An embodiment of the present disclosure further provides a computer-readable storage medium, which stores computer instructions. When the computer instructions are executed on a processor, the processor executes the technical solution of the test method for unmanned equipment in the above embodiment.

[0151] The embodiments of the present disclosure further provide a computer program product, including a computer program, which, when executed by a processor, is used to execute the technical solution of the test method for unmanned equipment in the above embodiment.

[0152] The computer-readable storage medium may be implemented by any type of volatile or non-volatile memory device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The computer-readable storage medium may be any available medium that can be accessed by a general-purpose or dedicated server.

[0153] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

[0154] Although the present disclosure is disclosed as above in terms of preferred embodiments, it is not intended to limit the present disclosure. Any person skilled in the art may make possible changes and modifications without departing from the spirit and scope of the present disclosure. Therefore, the scope of protection of the present disclosure shall be based on the scope defined by the claims of the present disclosure.

Claims

1. A testing method for unmanned equipment, characterized in that: The unmanned equipment is equipped with an auxiliary device for unmanned driving of the unmanned equipment, the auxiliary device is connected to a host computer, the auxiliary device includes a data acquisition device, and the method is applied to the host computer, the method includes: receiving first data of the unmanned device output by the data acquisition device, and processing the first data according to an input data type of a control program for unmanned driving of the unmanned device to obtain second data having the input data type; determining a first data frequency of the data acquisition device according to the first data; Determining whether the data acquisition device has a hardware protocol level fault according to the first data frequency; determining a second data frequency of the data acquisition device according to the second data, and reading target data corresponding to a process in which the unmanned equipment performs a preset action from the second data; It is determined whether the data acquisition device has a data drive level fault according to the second data frequency and the target data.

2. The method according to claim 1, characterized in that The determining, based on the first data frequency, whether the data acquisition device has a hardware protocol level fault includes: determining whether the first data frequency is within a first frequency range preset for the data acquisition device; If the first data frequency is within the first frequency range preset for the data acquisition device, it is determined that there is no hardware protocol level failure in the data acquisition device.

3. The method according to claim 2, characterized in that The determining, based on the first data frequency, whether the data acquisition device has a hardware protocol level fault includes: If the first data frequency is not within the first frequency range preset for the data acquisition device, it is determined that a hardware protocol level fault exists in the data acquisition device.

4. The method according to claim 2, characterized in that The method of determining a second data frequency of the data acquisition device according to the second data, and reading target data corresponding to a process of the unmanned equipment performing a preset action in the second data, further includes: If the first data frequency is within the first frequency range preset for the data acquisition device, the second data frequency of the data acquisition device is determined according to the second data, and the target data corresponding to the process of the unmanned equipment performing the preset action is read in the second data.

5. The method according to claim 1, wherein The determining, based on the second data frequency and the target data, whether the data acquisition device has a data drive level fault includes: determining whether the target data differs from a preset reference data for the data acquisition device by more than a preset error range, and determining whether the second data frequency is within a second frequency range preset for the data acquisition device; If the target data does not differ from the benchmark data preset for the data acquisition device by more than the preset error range, and the second data frequency is within the second frequency range preset for the data acquisition device, it is determined that there is no data-driven fault in the data acquisition device.

6. The method according to claim 5, characterized in that The determining, based on the second data frequency and the target data, whether the data acquisition device has a data drive level fault further includes: If the target data differs from the benchmark data preset for the data acquisition device by more than the preset error range, or the second data frequency is not within the second frequency range preset for the data acquisition device, it is determined that there is a data drive level fault in the data acquisition device.

7. The method according to claim 1, characterized in that The auxiliary device includes a lower computer, which is connected to the unmanned device and is used to control the unmanned device to perform an action in response to a control instruction received from the upper computer. The method further includes: generating a target control instruction for controlling the unmanned equipment to perform a target action according to an output instruction type of the control program; Sending the target control instruction to the lower computer, so that the lower computer controls the unmanned equipment to perform an action in response to the target control instruction; determining an action performed by the unmanned device; Determine whether the lower computer has a fault based on the actions performed by the unmanned equipment.

8. The method according to claim 7, characterized in that The determining whether the lower computer has a fault according to the action performed by the unmanned equipment includes: Determining whether the action performed by the unmanned device is the target action; If the action performed by the unmanned equipment is the target action, it is determined that there is no fault in the lower computer.

9. The method according to claim 8, characterized in that The determining whether the lower computer has a fault according to the action performed by the unmanned equipment further includes: If the action performed by the unmanned equipment is not the target action, it is determined that the lower computer has a fault.

10. The method according to any one of claims 1 to 9, characterized in that The data acquisition device includes one or more of the following: a sensor, a measuring encoder, a speedometer, and a photographing device.

11. A testing device for unmanned equipment, characterized in that: The unmanned equipment is equipped with an auxiliary device for unmanned driving of the unmanned equipment, the auxiliary device is connected to a host computer, the auxiliary device includes a data acquisition device, the test device for the unmanned equipment is deployed on the host computer, and the test device for the unmanned equipment includes: a data receiving and processing module, configured to receive first data of the unmanned device output by the data acquisition device, and process the first data according to an input data type of a control program for unmanned driving of the unmanned device to obtain second data having the input data type; a frequency determination module, configured to determine a first data frequency of the data acquisition device according to the first data; a first judging module, configured to judge whether the data acquisition device has a hardware protocol fault according to the first data frequency; a frequency determination and data reading module, configured to determine a second data frequency of the data acquisition device according to the second data, and to read target data corresponding to a process in which the unmanned equipment performs a preset action in the second data; The second judgment module is used to judge whether the data acquisition device has a data drive level fault according to the second data frequency and the target data.

12. An electronic device, characterized in that: include: a processor, a memory, and computer program instructions stored on the memory and executable on the processor; When the processor executes the computer program instructions, the testing method for unmanned equipment as described in any one of claims 1 to 10 is implemented.

13. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer program instructions, which, when executed by a processor, are used to implement the test method for unmanned equipment as described in any one of claims 1 to 10 above.

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